Internet DRAFT - draft-gont-numeric-ids-generation
draft-gont-numeric-ids-generation
Network Working Group F. Gont
Internet-Draft SI6 Networks
Intended status: Best Current Practice I. Arce
Expires: January 9, 2020 Quarkslab
July 8, 2019
On the Generation of Transient Numeric Identifiers
draft-gont-numeric-ids-generation-04
Abstract
This document performs an analysis of the security and privacy
implications of different types of "numeric identifiers" used in IETF
protocols, and tries to categorize them based on their
interoperability requirements and the associated failure severity
when such requirements are not met. Subsequently, it provides advice
on possible algorithms that could be employed to satisfy the
interoperability requirements of each identifier type, while
minimizing the security and privacy implications, thus providing
guidance to protocol designers and protocol implementers. Finally,
this describes a number of algorithms that have been employed in real
implementations to generate transient numeric identifiers and
analyzes their security and privacy properties.
Status of This Memo
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Copyright Notice
Copyright (c) 2019 IETF Trust and the persons identified as the
document authors. All rights reserved.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 4
3. Threat Model . . . . . . . . . . . . . . . . . . . . . . . . 5
4. Issues with the Specification of Identifiers . . . . . . . . 5
5. Protocol Failure Severity . . . . . . . . . . . . . . . . . . 6
6. Categorizing Identifiers . . . . . . . . . . . . . . . . . . 6
7. Common Algorithms for Identifier Generation . . . . . . . . . 9
7.1. Category #1: Uniqueness (soft failure) . . . . . . . . . 9
7.2. Category #2: Uniqueness (hard failure) . . . . . . . . . 10
7.3. Category #3: Uniqueness, constant within context (soft-
failure) . . . . . . . . . . . . . . . . . . . . . . . . 10
7.4. Category #4: Uniqueness, monotonically increasing within
context (hard failure) . . . . . . . . . . . . . . . . . 12
8. Common Vulnerabilities Associated with Transient Numeric
Identifiers . . . . . . . . . . . . . . . . . . . . . . . . . 17
8.1. Network Activity Correlation . . . . . . . . . . . . . . 17
8.2. Information Leakage . . . . . . . . . . . . . . . . . . . 17
8.3. Exploitation of Semantics of Transient Numeric
Identifiers . . . . . . . . . . . . . . . . . . . . . . . 19
8.4. Exploitation of Collisions of Transient Numeric
Identifiers . . . . . . . . . . . . . . . . . . . . . . . 19
9. Vulnerability Analysis of Specific Transient Numeric
Identifiers Categories . . . . . . . . . . . . . . . . . . . 19
9.1. Category #1: Uniqueness (soft failure) . . . . . . . . . 19
9.2. Category #2: Uniqueness (hard failure) . . . . . . . . . 20
9.3. Category #3: Uniqueness, constant within context (soft
failure) . . . . . . . . . . . . . . . . . . . . . . . . 20
9.4. Category #4: Uniqueness, monotonically increasing within
context (hard failure) . . . . . . . . . . . . . . . . . 20
10. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 22
11. Security Considerations . . . . . . . . . . . . . . . . . . . 22
12. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 23
13. References . . . . . . . . . . . . . . . . . . . . . . . . . 23
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13.1. Normative References . . . . . . . . . . . . . . . . . . 23
13.2. Informative References . . . . . . . . . . . . . . . . . 24
Appendix A. Flawed Algorithms . . . . . . . . . . . . . . . . . 27
A.1. Predictable Linear Identifiers Algorithm . . . . . . . . 27
A.2. Random-Increments Algorithm . . . . . . . . . . . . . . . 28
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 30
1. Introduction
Network protocols employ a variety of numeric identifiers for
different protocol entities, ranging from DNS Transaction IDs (TxIDs)
to transport protocol ports (e.g. TCP ports) or IPv6 Interface
Identifiers (IIDs). These identifiers usually have specific
properties that must be satisfied such that they do not result in
negative interoperability implications (e.g. uniqueness during a
specified period of time), and an associated failure severity when
such properties are not met, ranging from soft to hard failures.
For more than 30 years, a large number of implementations of the TCP/
IP protocol suite have been subject to a variety of attacks, with
effects ranging from Denial of Service (DoS) or data injection, to
information leakage that could be exploited for pervasive monitoring
[RFC7258]. The root of these issues has been, in many cases, the
poor selection of identifiers in such protocols, usually as a result
of insufficient or misleading specifications. While it is generally
trivial to identify an algorithm that can satisfy the
interoperability requirements of a given identifier, there exists
practical evidence that doing so without negatively affecting the
security and/or privacy properties of the aforementioned protocols is
prone to error [I-D.gont-numeric-ids-history].
For example, implementations have been subject to security and/or
privacy issues resulting from:
o Predictable TCP sequence numbers
o Predictable transport protocol port numbers
o Predictable IPv4 or IPv6 Fragment Identifiers
o Predictable IPv6 Interface Identifiers (IIDs)
o Predictable DNS Transaction Identifiers (TxIDs)
Recent history indicates that when new protocols are standardized or
new protocol implementations are produced, the security and privacy
properties of the associated identifiers tend to be overlooked and
inappropriate algorithms to generate transient numeric identifiers
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are either suggested in the specification or selected by
implementers. As a result, we believe that advice in this area is
warranted.
This document contains a non-exhaustive survey of identifiers
employed in various IETF protocols, and aims to categorize such
identifiers based on their interoperability requirements, and the
associated failure severity when such requirements are not met.
Subsequently, it provides advice on possible algorithms that could be
employed to satisfy the interoperability requirements of each
category, while minimizing the associated security and privacy
implications. Finally, it analyzes several algorithms that have been
employed in real implementations to meet such requirements and
analyzes their security and privacy properties.
2. Terminology
Identifier:
A data object in a protocol specification that can be used to
definitely distinguish a protocol object (a datagram, network
interface, transport protocol endpoint, session, etc) from all
other objects of the same type, in a given context. Identifiers
are usually defined as a series of bits and represented using
integer values. We note that different identifiers may have
additional requirements or properties depending on their specific
use in a protocol. We use the term "identifier" as a generic term
to refer to any data object in a protocol specification that
satisfies the identification property stated above.
Failure Severity:
The consequences of a failure to comply with the interoperability
requirements of a given identifier. Severity considers the worst
potential consequence of a failure, determined by the system
damage and/or time lost to repair the failure. In this document
we define two types of failure severity: "soft" and "hard".
Hard Failure:
A hard failure is a non-recoverable condition in which a protocol
does not operate in the prescribed manner or it operates with
excessive degradation of service. For example, an established TCP
connection that is aborted due to an error condition constitutes,
from the point of view of the transport protocol, a hard failure,
since it enters a state from which normal operation cannot be
recovered.
Soft Failure:
A soft failure is a recoverable condition in which a protocol does
not operate in the prescribed manner but normal operation can be
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resumed automatically in a short period of time. For example, a
simple packet-loss event that is subsequently recovered with a
retransmission can be considered a soft failure.
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119].
3. Threat Model
Throughout this document, we assume an attacker does not have
physical or logical access to the device(s) being attacked. We
assume the attacker can simply send any traffic to the target
devices, to e.g. sample identifiers employed by such devices.
4. Issues with the Specification of Identifiers
While assessing protocol specifications regarding the use of
identifiers, we found that most of the issues discussed in this
document arise as a result of one of the following conditions:
o Protocol specifications which under-specify the requirements for
their identifiers
o Protocol specifications that over-specify their identifiers
o Protocol implementations that simply fail to comply with the
specified requirements
A number of protocol implementations (too many of them) simply
overlook the security and privacy implications of identifiers
[I-D.gont-numeric-ids-history]. Examples of them are the
specification of TCP port numbers in [RFC0793], the specification of
TCP sequence numbers in [RFC0793], or the specification of the DNS
TxID in [RFC1035].
On the other hand, there are a number of protocol specifications that
over-specify some of their associated protocol identifiers. For
example, [RFC4291] essentially results in link-layer addresses being
embedded in the IPv6 Interface Identifiers (IIDs) when the
interoperability requirement of uniqueness could be achieved in other
ways that do not result in negative security and privacy implications
[RFC7721]. Similarly, [RFC2460] suggested the use of a global
counter for the generation of Fragment Identification values, when
the interoperability properties of uniqueness per {Src IP, Dst IP}
could be achieved with other algorithms that do not result in
negative security and privacy implications.
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Finally, there are protocol implementations that simply fail to
comply with existing protocol specifications. For example, some
popular operating systems (notably Microsoft Windows) still fail to
implement transport port randomization, as specified in [RFC6056].
5. Protocol Failure Severity
Section 2 defines the concept of "Failure Severity" and two types of
failures that we employ throughout this document: soft and hard.
Our analysis of the severity of a failure is performed from the point
of view of the protocol in question. However, the corresponding
severity on the upper application or protocol may not be the same as
that of the protocol in question. For example, a TCP connection that
is aborted may or may not result in a hard failure of the upper
application: if the upper application can establish a new TCP
connection without any impact on the application, a hard failure at
the TCP protocol may have no severity at the application level. On
the other hand, if a hard failure of a TCP connection results in
excessive degradation of service at the application layer, it will
also result in a hard failure at the application.
6. Categorizing Identifiers
This section includes a non-exhaustive survey of identifiers, and
proposes a number of categories that can accommodate these
identifiers based on their interoperability requirements and their
failure modes (soft or hard)
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+------------+--------------------------------------+---------------+
| Identifier | Interoperability Requirements | Failure |
| | | Severity |
+------------+--------------------------------------+---------------+
| IPv6 Frag | Uniqueness (for IP address pair) | Soft/Hard (1) |
| ID | | |
+------------+--------------------------------------+---------------+
| IPv6 IID | Uniqueness (and constant within IPv6 | Soft (3) |
| | prefix) (2) | |
+------------+--------------------------------------+---------------+
| TCP ISN | Monotonically-increasing | Hard (4) |
+------------+--------------------------------------+---------------+
| TCP eph. | Uniqueness (for connection ID) | Hard |
| port | | |
+------------+--------------------------------------+---------------+
| IPv6 Flow | Uniqueness | None (5) |
| L. | | |
+------------+--------------------------------------+---------------+
| DNS TxID | Uniqueness | None (6) |
+------------+--------------------------------------+---------------+
Table 1: Survey of Identifiers
Notes:
(1)
While a single collision of Fragment ID values would simply lead
to a single packet drop (and hence a "soft" failure), repeated
collisions at high data rates might trash the Fragment ID space,
leading to a hard failure [RFC4963].
(2)
While the interoperability requirements are simply that the
Interface ID results in a unique IPv6 address, for operational
reasons it is typically desirable that the resulting IPv6 address
(and hence the corresponding Interface ID) be constant within each
network [RFC7217] [RFC8064] .
(3)
While IPv6 Interface IDs must result in unique IPv6 addresses,
IPv6 Duplicate Address Detection (DAD) [RFC4862] allows for the
detection of duplicate Interface IDs/addresses, and hence such
Interface ID collisions can be recovered.
(4)
In theory there are no interoperability requirements for TCP
Initial Sequence Numbers (ISNs), since the TIME-WAIT state and
TCP's "quiet time" take care of old segments from previous
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incarnations of the connection. However, a widespread
optimization allows for a new incarnation of a previous connection
to be created if the ISN of the incoming SYN is larger than the
last sequence number seen in that direction for the previous
incarnation of the connection. Thus, monotonically-increasing TCP
sequence numbers allow for such optimization to work as expected
[RFC6528].
(5)
The IPv6 Flow Label is typically employed for load sharing
[RFC7098], along with the Source and Destination IPv6 addresses.
Reuse of a Flow Label value for the same set {Source Address,
Destination Address} would typically cause both flows to be
multiplexed into the same link. However, as long as this does not
occur deterministically, it will not result in any negative
implications.
(6)
DNS TxIDs are employed, together with the Source Address,
Destination Address, Source Port, and Destination Port, to match
DNS requests and responses. However, since an implementation
knows which DNS requests were sent for that set of {Source
Address, Destination Address, Source Port, and Destination Port,
DNS TxID}, a collision of TxID would result, if anything, in a
small performance penalty (the response would be discarded when it
is found that it does not answer the query sent in the
corresponding DNS query).
Based on the survey above, we can categorize identifiers as follows:
+-----+---------------------------------------+---------------------+
| Cat | Category | Sample Proto IDs |
| # | | |
+-----+---------------------------------------+---------------------+
| 1 | Uniqueness (soft failure) | IPv6 Flow L., DNS |
| | | TxIDs |
+-----+---------------------------------------+---------------------+
| 2 | Uniqueness (hard failure) | IPv6 Frag ID, TCP |
| | | ephemeral port |
+-----+---------------------------------------+---------------------+
| 3 | Uniqueness, constant within context | IPv6 IIDs |
| | (soft failure) | |
+-----+---------------------------------------+---------------------+
| 4 | Uniqueness, monotonically increasing | TCP ISN |
| | within context (hard failure) | |
+-----+---------------------------------------+---------------------+
Table 2: Identifier Categories
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We note that Category #4 could be considered a generalized case of
category #3, in which a monotonically increasing element is added to
a constant (within context) element, such that the resulting
identifiers are monotonically increasing within a specified context.
That is, the same algorithm could be employed for both #3 and #4,
given appropriate parameters.
7. Common Algorithms for Identifier Generation
The following subsections describe common algorithms found for
Protocol ID generation for each of the categories above.
7.1. Category #1: Uniqueness (soft failure)
7.1.1. Simple Randomization Algorithm
/* Ephemeral port selection function */
id_range = max_id - min_id + 1;
next_id = min_id + (random() % id_range);
count = next_id;
do {
if(check_suitable_id(next_id))
return next_id;
if (next_id == max_id) {
next_id = min_id;
} else {
next_id++;
}
count--;
} while (count > 0);
return ERROR;
Note:
random() is a function that returns a pseudo-random unsigned
integer number of appropriate size. Note that the output needs to
be unpredictable, and typical implementations of POSIX random()
function do not necessarily meet this requirement. See [RFC4086]
for randomness requirements for security.
The function check_suitable_id() can check, when possible, whether
this identifier is e.g. already in use. When already used, this
algorithm selects the next available protocol ID.
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All the variables (in this and all the algorithms discussed in
this document) are unsigned integers.
This algorithm does not suffer from any of the issues discussed in
Section 8.
7.1.2. Another Simple Randomization Algorithm
The following pseudo-code illustrates another algorithm for selecting
a random identifier in which, in the event the identifier is found to
be not suitable (e.g., already in use), another identifier is
selected randomly:
id_range = max_id - min_id + 1;
next_id = min_id + (random() % id_range);
count = id_range;
do {
if(check_suitable_id(next_id))
return next_id;
next_id = min_id + (random() % id_range);
count--;
} while (count > 0);
return ERROR;
This algorithm might be unable to select an identifier (i.e., return
"ERROR") even if there are suitable identifiers available, when there
are a large number of identifiers "in use".
This algorithm does not suffer from any of the issues discussed in
Section 8.
7.2. Category #2: Uniqueness (hard failure)
One of the most trivial approaches for achieving uniqueness for an
identifier (with a hard failure mode) is to implement a linear
function. As a result, all of the algorithms described in
Section 7.4 are of use for complying the requirements of this
identifier category.
7.3. Category #3: Uniqueness, constant within context (soft-failure)
The goal of this algorithm is to produce identifiers that are
constant for a given context, but that change when the aforementioned
context changes.
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Keeping one value for each possible "context" may in many cases be
considered too onerous in terms of memory requirements. As a
workaround, the following algorithm employs a calculated technique
(as opposed to keeping state in memory) to maintain the constant
identifier for each given context.
In the following algorithm, the function F() provides (statelessly) a
constant identifier for each given context.
/* Protocol ID selection function */
id_range = max_id - min_id + 1;
counter = 0;
do {
offset = F(CONTEXT, counter, secret_key);
next_id = min_id + (offset % id_range);
if(check_suitable_id(next_id))
return next_id;
counter++;
} while (counter <= MAX_RETRIES);
return ERROR;
The function F() provides a "per-CONTEXT" constant identifier for a
given context. 'offset' may take any value within the storage type
range since we are restricting the resulting identifier to be in the
range [min_id, max_id] in a similar way as in the algorithm described
in Section 7.1.1. Collisions can be recovered by incrementing the
'counter' variable and recomputing F().
The function F() should be a cryptographic hash function like SHA-256
[FIPS-SHS]. Note: MD5 [RFC1321] is considered unacceptable for F()
[RFC6151]. CONTEXT is the concatenation of all the elements that
define a given context. For example, if this algorithm is expected
to produce identifiers that are unique per network interface card
(NIC) and SLAAC autoconfiguration prefix, the CONTEXT should be the
concatenation of e.g. the interface index and the SLAAC
autoconfiguration prefix (please see [RFC7217] for an implementation
of this algorithm for the generation of IPv6 IIDs).
The secret should be chosen to be as random as possible (see
[RFC4086] for recommendations on choosing secrets).
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For obvious reasons, the transient network identifiers generated with
this algorithm allow for network activity correlation within
"CONTEXT". However, this is essentially a design goal of this
category of transient numeric identifiers.
7.4. Category #4: Uniqueness, monotonically increasing within context
(hard failure)
7.4.1. Per-context Counter Algorithm
One possible way to achieve low identifier reuse frequency while
still avoiding predictable sequences would be to employ a per-context
counter, as opposed to a global counter. Such an algorithm could be
described as follows:
/* Initialization at system boot time. Could be random */
id_inc= 1;
/* Identifier selection function */
count = max_id - min_id + 1;
if(lookup_counter(CONTEXT) == ERROR){
create_counter(CONTEXT);
}
next_id= lookup_counter(CONTEXT);
do {
if (next_id == max_id) {
next_id = min_id;
}
else {
next_id = next_id + id_inc;
}
if (check_suitable_id(next_id)){
store_counter(CONTEXT, next_id);
return next_id;
}
count--;
} while (count > 0);
store_counter(CONTEXT, next_id);
return ERROR;
NOTE:
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lookup_counter() returns the current counter for a given context,
or an error condition if such a counter does not exist.
create_counter() creates a counter for a given context, and
initializes such counter to a random value.
store_counter() saves (updates) the current counter for a given
context.
check_suitable_id() is a function that checks whether the
resulting identifier is acceptable (e.g., whether its in use,
etc.).
Essentially, whenever a new identifier is to be selected, the
algorithm checks whether there there is a counter for the
corresponding context. If there is, such counter is incremented to
obtain the new identifier, and the new identifier updates the
corresponding counter. If there is no counter for such context, a
new counter is created an initialized to a random value, and used as
the new identifier.
This algorithm produces a per-context counter, which results in one
linear function for each context. Since the origin of each "line" is
a random value, the resulting values are unknown to an off-path
attacker.
This algorithm has the following drawbacks:
o If, as a result of resource management, the counter for a given
context must be removed, the last identifier value used for that
context will be lost. Thus, if subsequently an identifier needs
to be generated for such context, that counter will need to be
recreated and reinitialized to random value, thus possibly leading
to reuse/collistion of identifiers.
o If the identifiers are predictable by the destination system
(e.g., the destination host represents the "context"), a
vulnerable host might possibly leak to third parties the
identifiers used by other hosts to send traffic to it (i.e., a
vulnerable Host B could leak to Host C the identifier values that
Host A is using to send packets to Host B). Appendix A of
[RFC7739] describes one possible scenario for such leakage in
detail.
Otherwise, the identifiers produced by this algorithm do not suffer
from the other issues discussed in Section 8.
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7.4.2. Simple Hash-Based Algorithm
The goal of this algorithm is to produce monotonically-increasing
sequences, with a randomized initial value, for each given context.
For example, if the identifiers being generated must be unique for
each {src IP, dst IP} set, then each possible combination of {src IP,
dst IP} should have a corresponding "next_id" value.
Keeping one value for each possible "context" may in many cases be
considered too onerous in terms of memory requirements. As a
workaround, the following algorithm employs a calculated technique
(as opposed to keeping state in memory) to maintain the random offset
for each possible context.
In the following algorithm, the function F() provides (statelessly) a
random offset for each given context.
/* Initialization at system boot time. Could be random. */
counter = 0;
/* Protocol ID selection function */
id_range = max_id - min_id + 1;
offset = F(CONTEXT, secret_key);
count = id_range;
do {
next_id = min_id +
(counter + offset) % id_range;
counter++;
if(check_suitable_id(next_id))
return next_id;
count--;
} while (count > 0);
return ERROR;
The function F() provides a "per-CONTEXT" fixed offset within the
identifier space. Both the 'offset' and 'counter' variables may take
any value within the storage type range since we are restricting the
resulting identifier to be in the range [min_id, max_id] in a similar
way as in the algorithm described in Section 7.1.1. This allows us
to simply increment the 'counter' variable and rely on the unsigned
integer to wrap around.
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The function F() should be a cryptographic hash function like SHA-256
[FIPS-SHS]. Note: MD5 [RFC1321] is considered unacceptable for F()
[RFC6151]. CONTEXT is the concatenation of all the elements that
define a given context. For example, if this algorithm is expected
to produce identifiers that are monotonically-increasing for each set
(Source IP Address, Destination IP Address), the CONTEXT should be
the concatenation of these two values.
The secret should be chosen to be as random as possible (see
[RFC4086] for recommendations on choosing secrets).
It should be noted that, since this algorithm uses a global counter
("counter") for selecting identifiers, this algorithm produces an
information leakage (as described in Section 8.2). For example, if
this algorithm were used for TCP ephemeral port selection, and an
attacker could force a client to periodically establish a new TCP
connection to an attacker-controlled machine (or through an attacker-
observable routing path), the attacker could subtract consecutive
source port values to obtain the number of outgoing TCP connections
established globally by the target host within that time period (up
to wrap-around issues and five-tuple collisions, of course).
7.4.3. Double-Hash Algorithm
A trade-off between maintaining a single global 'counter' variable
and maintaining 2**N 'counter' variables (where N is the width of the
result of F()) could be achieved as follows. The system would keep
an array of TABLE_LENGTH integers, which would provide a separation
of the increment of the 'counter' variable. This improvement could
be incorporated into the algorithm from Section 7.4.2 as follows:
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/* Initialization at system boot time */
for(i = 0; i < TABLE_LENGTH; i++)
table[i] = random();
id_inc = 1;
/* Protocol ID selection function */
id_range = max_id - min_id + 1;
offset = F(CONTEXT, secret_key1);
index = G(CONTEXT, secret_key2);
count = id_range;
do {
next_id = min_id + (offset + table[index]) % id_range;
table[index] = table[index] + id_inc;
if(check_suitable_id(next_id))
return next_id;
count--;
} while (count > 0);
return ERROR;
'table[]' could be initialized with random values, as indicated by
the initialization code in pseudo-code above. The function G()
should be a cryptographic hash function. It should use the same
CONTEXT as F(), and a secret key value to compute a value between 0
and (TABLE_LENGTH-1).
The array 'table[]' assures that successive identifiers for a given
context will be monotonically-increasing. However, the increments
space is separated into TABLE_LENGTH different spaces, and thus
identifier reuse frequency will be (probabilistically) lower than
that of the algorithm in Section 7.4.2. That is, the generation of
identifier for one given context will not necessarily result in
increments in the identifiers for other contexts.
It is interesting to note that the size of 'table[]' does not limit
the number of different identifier sequences, but rather separates
the *increments* into TABLE_LENGTH different spaces. The identifier
sequence will result from adding the corresponding entry of 'table[]'
to the variable 'offset', which selects the actual identifier
sequence (as in the algorithm from Section 7.4.2).
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An attacker can perform traffic analysis for any "increment space"
(i.e., context) into which the attacker has "visibility" -- namely,
the attacker can force a node to generate identifiers where G(offset)
identifies the target "increment space". However, the attacker's
ability to perform traffic analysis is very reduced when compared to
the predictable linear identifiers (described in Appendix A.1) and
the hash-based identifiers (described in Section 7.4.2).
Additionally, an implementation can further limit the attacker's
ability to perform traffic analysis by further separating the
increment space (that is, using a larger value for TABLE_LENGTH) and/
or by randomizing the increments.
Otherwise, this algorithm does not suffer from the issues discussed
in Section 8.
8. Common Vulnerabilities Associated with Transient Numeric Identifiers
8.1. Network Activity Correlation
An identifier that is predictable or stable within a given context
allows for network activity correlation within that context.
For example, a stable IPv6 Interface Identifier allows for network
activity to be correlated for the context in which that address is
stable [RFC7721]. A stable-per-network (as in [RFC7217] allows for
network activity correlation within a network, whereas a constant
IPv6 Interface Identifier allows not only network activity
correlation within the same network, but also across networks ("host
tracking").
Predictable transient numeric identifiers can also allow for network
activity correlation. For example, a node that generates TCP ISNs
with a global counter will typically allow network activity
correlation even as it roams across networks, since the communicating
nodes could infer the identity of the node based on the TCP ISNs
employed for subsequent communication instances. Similarly, a node
that generates predictable IPv6 Fragment Identification values could
be subject to network activity correlation (see e.g.
[Bellovin2002]).
8.2. Information Leakage
Transient numeric identifiers that are not randomized can leak out
information to other communicating nodes. For example, it is common
to generate identifiers like:
ID = offset(CONTEXT_1) + linear(CONTEXT_2);
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This generic expression generates identifiers by adding a linear
function to an offset. The offset is constant within a given
context, whereas linear() is a linear function for a given context
(possibly different to that of offset()). Identifiers generated with
this expression will generally be predictable within CONTEXT_1.
Thus, CONTEXT_1 essentially specifies e.g. the context within which
network activity correlation is possible thanks to these identifiers.
When CONTEXT_1 is "global" (e.g., offset() is simply a constant
value), then all the corresponding transient numeric identifiers
become predictable in all contexts.
NOTE: If offset() has a global context and the specific value is
known, the resulting identifiers may leak even more information.
For example, the if Fragment Identification values are generated
with the generic function above, and CONTEXT_1 is "global", then
the corresponding identifiers will leak the number of fragmented
datagrams sent for CONTEXT_2. If both CONTEXT_1 and CONTEXT_2 are
"global", then Fragment Identification values would be generated
with a global counter (initialized to offset()), and thus each
generated Fragment Identification value would leak the number of
fragmented datagrams transmitted by the node since it was
bootstrapped.
On the other hand, linear() will be predictable within CONTEXT_2.
The predictability of linear(), irrespective of the context and/or
predictability of offset(), can leak out information that is of use
to attackers. For example, a node that selects ephemeral port
numbers on as in:
ehemeral_port = offset(Dest_IP) + linear()
that is, with a per-destination offset, but global linear() function
(e.g., a global counter), will leak information about the number of
outgoing connections that have been issued between any two issued
outgoing connections.
Similarly, a node that generates Fragment Identification values as
in:
Frag_ID = offset(Srd_IP, Dst_IP) + linear()
will leak out information about the number of fragmented packets that
have been transmitted between any two other transmitted fragmented
packets. The vulnerabilities described in [Sanfilippo1998a],
[Sanfilippo1998b], and [Sanfilippo1999] are all associated with the
use of a global linear() function (i.e., a global CONTEXT_2).
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8.3. Exploitation of Semantics of Transient Numeric Identifiers
Identifiers that are not semantically opaque tend to be more
predictable than semantically-opaque identifiers. For example, a MAC
address contains an OUI (Organizationally-Unique Identifier) which
identifies the vendor that manufactured the underlying network
interface card. This fact may be leveraged by an attacker meaning to
"predict" MAC addresses, if he has some knowledge about the possible
NIC vendor.
[RFC7707] discusses a number of techniques to reduce the search space
when performing IPv6 address-scanning attacks by leveraging the
semantics of the IIDs produced by a number by traditional IID-
generation algorithms (now replaced by [RFC8064] with [RFC7217]).
8.4. Exploitation of Collisions of Transient Numeric Identifiers
In many cases, th collision of transient network identifiers can have
a hard failure severity (or result in a hard failure severity if an
attacker can cause multiple collisions deterministically, one after
another). For example, predictable Fragment Identification values
open the door to Denial of Service (DoS) attacks (see e.g.
[RFC5722]. Similarly, predictable TCP ISNs open the door to trivial
connection-reset and data injection attacks (see e.g.
[Joncheray1995]).
9. Vulnerability Analysis of Specific Transient Numeric Identifiers
Categories
The following subsections analyze common vulnerabilities associated
with the generation of identifiers for each of the categories
identified in Section 6.
9.1. Category #1: Uniqueness (soft failure)
Possible vulnerabilities associated with identifiers of this category
are:
o Use of trivial algorithms (e.g. global counters) that generate
predictable identifiers
o Use of flawed PRNGs (please see e.g. [Zalewski2001],
[Zalewski2002] and [Klein2007])
Since the only interoperability requirement for these identifiers is
uniqueness, the obvious approach to generate them is to employ a
PRNG. An implementer should consult [RFC4086] regarding randomness
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requirements for security, and consult relevant documentation when
employing a PRNG provided by the underlying system.
Use of algorithms other than PRNGs for generating identifiers of this
category is discouraged.
9.2. Category #2: Uniqueness (hard failure)
As noted in Section 7.2 this category typically employs the same
algorithms as Category #4, since a monotonically-increasing sequence
tends to minimize the identifier reuse frequency. Therefore, the
vulnerability analysis of Section 9.4 applies to this case.
9.3. Category #3: Uniqueness, constant within context (soft failure)
There are two main vulnerabilities that may be associated with
identifiers of this category:
1. Use algorithms or sources that result in predictable identifiers
2. Employing the same identifier across contexts in which constantcy
is not required
At times, an implementation or specification may be tempted to employ
a source for the identifier which is known to provide unique values.
However, while unique, the associated identifiers may have other
properties such as being predictable or leaking information about the
node in question. For example, as noted in [RFC7721], embedding
link-layer addresses for generating IPv6 IIDs not only results in
predictable values, but also leaks information about the manufacturer
of the network interface card.
On the other hand, using an identifier across contexts where
constantcy is not required can be leveraged for correlation of
activities. On of the most trivial examples of this is the use of
IPv6 IIDs that are constant across networks (such as IIDs that embed
the underlying link-layer address).
9.4. Category #4: Uniqueness, monotonically increasing within context
(hard failure)
A simple way to generalize algorithms employed for generating
identifiers of Category #4 would be as follows:
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/* Identifier selection function */
count = max_id - min_id + 1;
do {
linear(CONTEXT_2)= linear(CONTEXT_2) + increment();
next_id= offset(CONTEXT_1) + linear(CONTEXT_2);
if(check_suitable_id(next_id))
return next_id;
count--;
} while (count > 0);
return ERROR;
Essentially, an identifier (next_id) is generated by adding a linear
function (linear()) to an offset value, which is unknown to the
attacker, and constant for given context (CONTEXT_1).
The following aspects of the algorithm should be considered:
o For the most part, it is the offset() function that results in
identifiers that are unpredictable by an off-path attacker. While
the resulting sequence will be monotonically-increasing, the use
of an offset value that is unknown to the attacker makes the
resulting values unknown to the attacker.
o The most straightforward "stateless" implementation of offset
would be that in which offset() is the result of a
cryptographically-secure hash-function that takes the values that
identify the context and a "secret_key" (not shown in the figure
above) as arguments.
o Another possible (but stateful) approach would be to simply
generate a random "per-context" offset and store it in memory, and
then look-up the corresponding context when a new identifier is to
be selected. The algorithm in Section 7.4.1 is essentially an
implementation of this type.
o The linear function is incremented according to increment(). In
the most trivial case increment() could always return the constant
"1". But it could also possibly return small random integers such
the increments are unpredictable.
Considering the generic algorithm illustrated above we can identify
the following possible vulnerabilities:
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o If the offset value spans more than the necessary context,
identifiers could be unnecessarily predictable by other parties,
since the offset value would be unnecessarily leaked to them. For
example, an implementation that means to produce a per-destination
counter but replaces offset() with a constant number (i.e.,
employs a global counter), will unnecessarily result in
predictable identifiers.
o The function linear() could be seen as representing the number of
identifiers that have so far been generated for a given context
(CONTEXT_2). If linear() spans more than the necessary context,
the "increments" could be leaked to other parties, thus disclosing
information about the number of identifiers that have so far been
generated. For example, an implementation in which linear() is
implemented as a single global counter will unnecessarily leak
information the number of identifiers that have been produced.
[Fyodor2004] is one example of how such information leakages can
be exploited.
o increment() determines how the linear() is incremented for each
identifier that is selected. In the most trivial case,
increment() will return the integer "1". However, an
implementation may have increment() return a "small" random
integer value such that even if the current value employed by the
generator is guessed (see Appendix A of [RFC7739]), the exact next
identifier to be selected will be slightly harder to identify.
10. IANA Considerations
There are no IANA registries within this document. The RFC-Editor
can remove this section before publication of this document as an
RFC.
11. Security Considerations
The entire document is about the security and privacy implications of
identifiers. [I-D.gont-numeric-ids-sec-considerations] formally
requires protocols specifications to include an appropriate analysis
of the interoperability, security, and privacy implications of the
transient numeric identifiers they specify, while this document
analyzes possible algorithms (and their implications) that could be
employed to comply with the interoperability properties of a
transient numeric identifier, while mitigating the possible security
and privacy implications.
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12. Acknowledgements
The authors would like to thank (in alphabetical order) Steven
Bellovin, Joseph Lorenzo Hall, Gre Norcie, and Martin Thomson, for
providing valuable comments on earlier versions of this document.
The authors would like to thank Diego Armando Maradona for his magic
and inspiration.
13. References
13.1. Normative References
[RFC0793] Postel, J., "Transmission Control Protocol", STD 7,
RFC 793, DOI 10.17487/RFC0793, September 1981,
<https://www.rfc-editor.org/info/rfc793>.
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997,
<https://www.rfc-editor.org/info/rfc2119>.
[RFC2460] Deering, S. and R. Hinden, "Internet Protocol, Version 6
(IPv6) Specification", RFC 2460, DOI 10.17487/RFC2460,
December 1998, <https://www.rfc-editor.org/info/rfc2460>.
[RFC4086] Eastlake 3rd, D., Schiller, J., and S. Crocker,
"Randomness Requirements for Security", BCP 106, RFC 4086,
DOI 10.17487/RFC4086, June 2005,
<https://www.rfc-editor.org/info/rfc4086>.
[RFC4291] Hinden, R. and S. Deering, "IP Version 6 Addressing
Architecture", RFC 4291, DOI 10.17487/RFC4291, February
2006, <https://www.rfc-editor.org/info/rfc4291>.
[RFC4862] Thomson, S., Narten, T., and T. Jinmei, "IPv6 Stateless
Address Autoconfiguration", RFC 4862,
DOI 10.17487/RFC4862, September 2007,
<https://www.rfc-editor.org/info/rfc4862>.
[RFC5722] Krishnan, S., "Handling of Overlapping IPv6 Fragments",
RFC 5722, DOI 10.17487/RFC5722, December 2009,
<https://www.rfc-editor.org/info/rfc5722>.
[RFC6528] Gont, F. and S. Bellovin, "Defending against Sequence
Number Attacks", RFC 6528, DOI 10.17487/RFC6528, February
2012, <https://www.rfc-editor.org/info/rfc6528>.
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[RFC7217] Gont, F., "A Method for Generating Semantically Opaque
Interface Identifiers with IPv6 Stateless Address
Autoconfiguration (SLAAC)", RFC 7217,
DOI 10.17487/RFC7217, April 2014,
<https://www.rfc-editor.org/info/rfc7217>.
[RFC8064] Gont, F., Cooper, A., Thaler, D., and W. Liu,
"Recommendation on Stable IPv6 Interface Identifiers",
RFC 8064, DOI 10.17487/RFC8064, February 2017,
<https://www.rfc-editor.org/info/rfc8064>.
13.2. Informative References
[Bellovin2002]
Bellovin, S., "A Technique for Counting NATted Hosts",
IMW'02 Nov. 6-8, 2002, Marseille, France, 2002.
[CPNI-TCP]
Gont, F., "Security Assessment of the Transmission Control
Protocol (TCP)", United Kingdom's Centre for the
Protection of National Infrastructure (CPNI) Technical
Report, 2009, <https://www.gont.com.ar/papers/
tn-03-09-security-assessment-TCP.pdf>.
[FIPS-SHS]
FIPS, "Secure Hash Standard (SHS)", Federal Information
Processing Standards Publication 180-4, March 2012,
<http://csrc.nist.gov/publications/fips/fips180-4/
fips-180-4.pdf>.
[Fyodor2004]
Fyodor, "Idle scanning and related IP ID games", 2004,
<http://www.insecure.org/nmap/idlescan.html>.
[I-D.gont-numeric-ids-history]
Gont, F. and I. Arce, "Unfortunate History of Transient
Numeric Identifiers", draft-gont-numeric-ids-history-04
(work in progress), March 2019.
[I-D.gont-numeric-ids-sec-considerations]
Gont, F. and I. Arce, "Security Considerations for
Transient Numeric Identifiers Employed in Network
Protocols", draft-gont-numeric-ids-sec-considerations-03
(work in progress), April 2019.
[Joncheray1995]
Joncheray, L., "A Simple Active Attack Against TCP", Proc.
Fifth Usenix UNIX Security Symposium, 1995.
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[Klein2007]
Klein, A., "OpenBSD DNS Cache Poisoning and Multiple O/S
Predictable IP ID Vulnerability", 2007,
<http://www.trusteer.com/files/OpenBSD_DNS_Cache_Poisoning
_and_Multiple_OS_Predictable_IP_ID_Vulnerability.pdf>.
[Morris1985]
Morris, R., "A Weakness in the 4.2BSD UNIX TCP/IP
Software", CSTR 117, AT&T Bell Laboratories, Murray Hill,
NJ, 1985,
<https://pdos.csail.mit.edu/~rtm/papers/117.pdf>.
[RFC1035] Mockapetris, P., "Domain names - implementation and
specification", STD 13, RFC 1035, DOI 10.17487/RFC1035,
November 1987, <https://www.rfc-editor.org/info/rfc1035>.
[RFC1321] Rivest, R., "The MD5 Message-Digest Algorithm", RFC 1321,
DOI 10.17487/RFC1321, April 1992,
<https://www.rfc-editor.org/info/rfc1321>.
[RFC4963] Heffner, J., Mathis, M., and B. Chandler, "IPv4 Reassembly
Errors at High Data Rates", RFC 4963,
DOI 10.17487/RFC4963, July 2007,
<https://www.rfc-editor.org/info/rfc4963>.
[RFC6056] Larsen, M. and F. Gont, "Recommendations for Transport-
Protocol Port Randomization", BCP 156, RFC 6056,
DOI 10.17487/RFC6056, January 2011,
<https://www.rfc-editor.org/info/rfc6056>.
[RFC6151] Turner, S. and L. Chen, "Updated Security Considerations
for the MD5 Message-Digest and the HMAC-MD5 Algorithms",
RFC 6151, DOI 10.17487/RFC6151, March 2011,
<https://www.rfc-editor.org/info/rfc6151>.
[RFC7098] Carpenter, B., Jiang, S., and W. Tarreau, "Using the IPv6
Flow Label for Load Balancing in Server Farms", RFC 7098,
DOI 10.17487/RFC7098, January 2014,
<https://www.rfc-editor.org/info/rfc7098>.
[RFC7258] Farrell, S. and H. Tschofenig, "Pervasive Monitoring Is an
Attack", BCP 188, RFC 7258, DOI 10.17487/RFC7258, May
2014, <https://www.rfc-editor.org/info/rfc7258>.
[RFC7707] Gont, F. and T. Chown, "Network Reconnaissance in IPv6
Networks", RFC 7707, DOI 10.17487/RFC7707, March 2016,
<https://www.rfc-editor.org/info/rfc7707>.
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[RFC7721] Cooper, A., Gont, F., and D. Thaler, "Security and Privacy
Considerations for IPv6 Address Generation Mechanisms",
RFC 7721, DOI 10.17487/RFC7721, March 2016,
<https://www.rfc-editor.org/info/rfc7721>.
[RFC7739] Gont, F., "Security Implications of Predictable Fragment
Identification Values", RFC 7739, DOI 10.17487/RFC7739,
February 2016, <https://www.rfc-editor.org/info/rfc7739>.
[Sanfilippo1998a]
Sanfilippo, S., "about the ip header id", Post to Bugtraq
mailing-list, Mon Dec 14 1998,
<http://seclists.org/bugtraq/1998/Dec/48>.
[Sanfilippo1998b]
Sanfilippo, S., "Idle scan", Post to Bugtraq mailing-list,
1998, <http://www.kyuzz.org/antirez/papers/dumbscan.html>.
[Sanfilippo1999]
Sanfilippo, S., "more ip id", Post to Bugtraq mailing-
list, 1999,
<http://www.kyuzz.org/antirez/papers/moreipid.html>.
[Shimomura1995]
Shimomura, T., "Technical details of the attack described
by Markoff in NYT", Message posted in USENET's
comp.security.misc newsgroup Message-ID:
<3g5gkl$5j1@ariel.sdsc.edu>, 1995,
<http://www.gont.com.ar/docs/post-shimomura-usenet.txt>.
[Silbersack2005]
Silbersack, M., "Improving TCP/IP security through
randomization without sacrificing interoperability",
EuroBSDCon 2005 Conference, 2005,
<http://citeseerx.ist.psu.edu/viewdoc/
download?doi=10.1.1.91.4542&rep=rep1&type=pdf>.
[Zalewski2001]
Zalewski, M., "Strange Attractors and TCP/IP Sequence
Number Analysis", 2001,
<http://lcamtuf.coredump.cx/oldtcp/tcpseq.html>.
[Zalewski2002]
Zalewski, M., "Strange Attractors and TCP/IP Sequence
Number Analysis - One Year Later", 2001,
<http://lcamtuf.coredump.cx/newtcp/>.
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Appendix A. Flawed Algorithms
The following subsections document algorithms with known negative
security and privacy implications.
A.1. Predictable Linear Identifiers Algorithm
One of the most trivial ways to achieve uniqueness with a low
identifier reuse frequency is to produce a linear sequence.
For example, the following algorithm has been employed (see e.g.
[Morris1985], [Shimomura1995], [Silbersack2005] and [CPNI-TCP]) in a
number of operating systems for selecting IP fragment IDs, TCP
ephemeral ports, etc.:
/* Initialization at system boot time. Could be random */
next_id = min_id;
id_inc= 1;
/* Identifier selection function */
count = max_id - min_id + 1;
do {
if (next_id == max_id) {
next_id = min_id;
}
else {
next_id = next_id + id_inc;
}
if (check_suitable_id(next_id))
return next_id;
count--;
} while (count > 0);
return ERROR;
Note:
check_suitable_id() is a function that checks whether the
resulting identifier is acceptable (e.g., whether its in use,
etc.).
For obvious reasons, this algorithm results in predicable sequences.
If a global counter is used (such as "next_id" in the example above),
a node that learns one protocol identifier can also learn or guess
values employed by past and future protocol instances. On the other
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hand, when the value of increments is known (such as "1" in this
case), an attacker can sample two values, and learn the number of
identifiers that were generated in-between.
Where identifier reuse would lead to a hard failure, one typical
approach to generate unique identifiers (while minimizing the
security and privacy implications of predictable identifiers) is to
obfuscate the resulting protocol IDs by either:
o Replace the global counter with multiple counters (initialized to
a random value)
o Randomizing the "increments"
Avoiding global counters essentially means that learning one
identifier for a given context (e.g., one TCP ephemeral port for a
given {src IP, Dst IP, Dst Port}) is of no use for learning or
guessing identifiers for a different context (e.g., TCP ephemeral
ports that involve other peers). However, this may imply keeping one
additional variable/counter per context, which may be prohibitive in
some environments. The choice of id_inc has implications on both the
security and privacy properties of the resulting identifiers, but
also on the corresponding interoperability properties. On one hand,
minimizing the increments (as in "id_inc = 1" in our case) generally
minimizes the identifier reuse frequency, albeit at increased
predictability. On the other hand, if the increments are randomized,
predictability of the resulting identifiers is reduced, and the
information leakage produced by global constant increments is
mitigated. However, using larger increments than necessary can
result in an increased identifier reuse frequency.
A.2. Random-Increments Algorithm
This algorithm offers a middle ground between the algorithms that
select ephemeral ports randomly (such as those described in
Section 7.1.1 and Section 7.1.2), and those that offer obfuscation
but no randomization (such as those described in Section 7.4.2 and
Section 7.4.3).
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/* Initialization code at system boot time. */
next_id = random(); /* Initialization value */
id_inc = 500; /* Determines the trade-off */
/* Identifier selection function */
id_range = max_id - min_id + 1;
count = id_range;
do {
/* Random increment */
next_id = next_id + (random() % id_inc) + 1;
/* Keep the identifier within acceptable range */
next_id = min_id + (next_id % id_range);
if(check_suitable_id(next_id))
return next_id;
count--;
} while (count > 0);
return ERROR;
This algorithm aims at producing a monotonically increasing sequence
of identifiers, while avoiding the use of fixed increments, which
would lead to trivially predictable sequences. The value "id_inc"
allows for direct control of the trade-off between the level of
obfuscation and the ID reuse frequency. The smaller the value of
"id_inc", the more similar this algorithm is to a predicable, global
monotonically-increasing ID generation algorithm. The larger the
value of "id_inc", the more similar this algorithm is to the
algorithm described in Section 7.1.1 of this document.
When the identifiers wrap, there is the risk of collisions of
identifiers (i.e., identifier reuse). Therefore, "id_inc" should be
selected according to the following criteria:
o It should maximize the wrapping time of the identifier space.
o It should minimize identifier reuse frequency.
o It should maximize obfuscation.
Clearly, these are competing goals, and the decision of which value
of "id_inc" to use is a trade-off. Therefore, the value of "id_inc"
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should be configurable so that system administrators can make the
trade-off for themselves.
Authors' Addresses
Fernando Gont
SI6 Networks
Evaristo Carriego 2644
Haedo, Provincia de Buenos Aires 1706
Argentina
Phone: +54 11 4650 8472
Email: fgont@si6networks.com
URI: https://www.si6networks.com
Ivan Arce
Quarkslab
Email: iarce@quarkslab.com
URI: https://www.quarkslab.com
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